>"It's part of the history of the field of artificial intelligence that every time somebody figured out how to make a computer do something—play good checkers, solve simple but relatively informal problems—there was a chorus of critics to say, 'that's not thinking'." AIS researcher Rodney Brooks complains: "Every time we figure out a piece of it, it stops being magical; we say, 'Oh, that's just a computation.'"
How about "the AI effect effect"?
This happens all the time:
- X suggests that success at a particular task is a good proxy to general intelligence.
- Years later Y solves that task with a clever hack and lots of computation, but no general intelligence.
- The media breathlessly suggests we've made progress on general intelligence.
- Z points out we haven't really.
- Someone says "Oh that's the AI effect!", by which they mean the goalposts have been unfairly moved on AI.
No, they have not. There's something called general intelligence, humans can do it, and Deep Blue cannot, and it's fine to say that Deep Blue beating humans at Chess was not thinking.
It just turned out that Chess wasn't as good a proxy to thinking as we initially thought, and mentioning "The AI effect" just clouds the discussion.
As AI is developed, it is also championed as "closer to real thought" and might someday solve the more general intelligence problem, only for those same experts to later realize that would never be the case and then retroactively proclaim "this was never going to solve general intelligence, but it is still AI".
The history is full of this kind of revisionism, so I agree with you.
That the current AI techniques couldn't work for every imaginable task, and that people believed they might isn't a case of the AI effect. That's just hype, and possibly another coming case of the AI freeze.
The AI effect will be how in 5 or 10 years, CS students will learn neural nets as part of their first or second year curriculum and the whole machinery will be behind a single API to some Apache library. And someone will then use that to some cool effect and say they're doing AI, and others will laugh and say, you're not doing AI, you just used a neural net to learn weights from a big data set silly, that's not AI.
This effect happens for every task, even when AI is not involved. Until you understand how, someone doing something you can't comprehend will have you think they are a genius and maybe of a higher IQ and probably very intelligent. But learn the "how" for yourself and it'll stop being so impressive. Rubik's cube is a good example of this. Once you realize there's a trick to it, it stops being as impressive.
Some relevant quotes from the wikipedia article:
> AI effect is: As soon as AI successfully solves a problem, the problem is no longer a part of AI.
> Software and algorithms developed by AI researchers are now integrated into many applications throughout the world, without really being called AI.
> AI advances are not trumpeted as artificial intelligence so much these days, but are often seen as advances in some other field
> practical AI successes, computational programs that actually achieved intelligent behavior, were soon assimilated into whatever application domain they were found to be useful in, and became silent partners alongside other problem-solving approaches, which left AI researchers to deal only with the "failures", the tough nuts that couldn't yet be cracked
> The great practical benefits of AI applications and even the existence of AI in many software products go largely unnoticed by many despite the already widespread use of AI techniques in software. This is the AI effect. Many marketing people don't use the term 'artificial intelligence' even when their company's products rely on some AI techniques. Why not?
While that is true the set that contains instances of Y is only growing and the members are each becoming less narrow.
Deepblue was only chess with many handcrafted parts. AlphaZero does chess, shogi and go with no prior knowledge. Then they went from perfect information, turn-based games to RTS with fog of war.
It's not general intelligence, but at least further down the road in behavioral complexity than jellyfish, despite some crippling limitations (e.g. separation of training and inference)
And when machines start to play chess (or go, or Starcraft) they just say "Oh well it's just computation."
So I think it's justified to bring up "AI effect" when people say "machines will never do $(insert your favorite activity here) because it requires general intelligence!"
It makes me think of the saying about atheism, that an atheism disbelieves just one more god out of thousands than a (mono)theist. You disbelieve in intelligence in very nearly all of the things it's been used to explain.
There's no such thing. General is a strong word. Humans can't for example handle more than 7 objects in working memory. We have an inbuilt limitation to how much complexity we can grasp. Programmers know what I mean.
General intelligence requires a general (infinitely complex and challenging) environment. Without it it will always be a specialised intelligence. Human intelligence is specialised in human survival, as individuals and part of society.
Also, we may not be able to keep some number N of objects in memory simultaneously, but we can definitely reason about an infinite number of objects, like I did above. And if you want to handle more than N objects, you just do it N objects at a time. You can always write things down etc.
You can always extend your memory, I mean.
Think about trying to explain the stock market to an ant. Then scale up, and imagine a similar situation for humans.
I think it would be very difficult to find a process that _cannot_ be understood by humans, let alon explain why. It'd be a bit of a paradox really. "Let me explain to you this thing that is impossible to understand".
Would it still be a general sorting algorithm if someone had just developed it and used it solely to sort numbers between 1 and 100?
It would be.
Why do you think you need to a general environment to develop a general algorithm?
No one is arguing human rationality is unbounded. But our intelligence generalizes, in a practical sense, to a great many more tasks than any computer algorithm I'm aware of.
Mainstream psychologists believe in general intelligence. They even attempt to measure components of it, with good prediction of performance on unseen tasks.
I think there's a big burden if you want to argue it doesn't exist.
Because intelligence is not intrinsic to the agent but the result of the agent trying to maximise rewards in an environment. In the end the driving force is survival - the agent needs only to survive, any method would do. So as soon as it overcomes a challenge it stops evolving and turns to exploiting. And the list of challenges that threaten survival does not scale to infinity. Anytime you think about intelligence you need to also think about the environment and the task otherwise it is meaningless.
citation needed
However stating "can't handle more than 7 objects in working memory" as fact seems a little too assertive to me :) Humans can do it, but are usually not very good at it as the number of items goes up.
There is progress, though. Machine learning does do a lot. And it makes money, so effort will continue at a high level. AI used to be a dinky field - maybe 20-50 people at MIT, CMU, and Stanford. Now it's huge.
But AI in its meaning use contains a certain set of fields in a way that makes sense. It's just the puplic misinterpration nonsense that makes it look so weird.
I’m happy to concede that software is artificially intelligent just as I’m prepared to concede that most animals are naturally intelligent. It’s just a question of drawing an arbitrary line when things are intelligent enough to warrant the description. The AI effect is the process of that line getting moved closer and closer to “capable of doing everything an average human can do.”
I guess it seems very likely to me that we will have Skynet/paperclip maximizers before AGI. I mean, I think we kind of do right now in what the internet is growing into.
We're like single cells imagining what a brain would be like but we'll never know because probably we'll be part of something brainless that dominates the ecosystem, or if there is an organism with a brain, we won't be able to perceive it because we're components.
So if it's not actually thinking, then technically, from the perspective of an average layperson, it is not real AI. However, the "AI effect" is still real, but it's related to a problem local to academics and AI laypeople.
Most non-AI-laypeople/AI academics believe AI is a machine that can think like how a person thinks.